A Photovoltaic Charging Control Method and System for a UAV Airport

Abstract

The present invention relates to the technical field of solar power supply distribution, and particularly relates to a photovoltaic charging control method and system for a drone airport. The present invention first obtains the preset inspection path, power consumption per unit inspection distance, remaining power of each drone, and the power supply available at the drone airport on the current day; further, it repeatedly obtains the drones to be charged and determines whether the power supply available at the airport on the current day can meet the inspection requirements of all drones; when it is determined that the power supply available on the current day cannot meet the inspection requirements of all drones, it obtains the local replaceability degree of the target segmented path, controls the deletion of the target segmented path, obtains the corrected inspection path of each drone to be charged, until it is determined that the power supply available on the current day can meet the inspection requirements of all drones, and obtains the final inspection path of each drone; finally, according to the final inspection path, remaining power, power consumption per unit inspection distance, and power supply available of each drone, power is allocated to each drone.

Description

Technical Field

[0001] The present invention relates to the technical field of solar power supply distribution, and particularly to a photovoltaic charging control method and system for an unmanned aerial vehicle (UAV) airport. Background Art

[0002] In a UAV airport, a photovoltaic power generation module is deployed to convert solar energy into electrical energy and transmit it to a energy storage module. The energy storage module can provide power for the UAV to perform inspection tasks, meeting the inspection power requirements of the UAV. However, the power that the energy storage module can provide is affected by weather conditions. For example, in sunny days with long sunshine hours compared to cloudy days with short sunshine hours, the efficiency and total amount of solar energy converted into electrical energy are higher, and the power that the energy storage module can provide is more sufficient.

[0003] Since the stored power of the energy storage module has an upper limit and the conversion of solar energy is affected by weather factors, there is a situation where the stored power and the remaining power of the UAV cannot meet the needs of all UAVs for a complete inspection. Therefore, how to intelligently control photovoltaic charging and reasonably allocate the stored power to ensure the inspection effect has become a key issue. Summary of the Invention

[0004] In order to solve the technical problem of intelligently controlling photovoltaic charging to ensure the inspection effect, the purpose of the present invention is to provide a photovoltaic charging control method and system for a UAV airport. The specific technical solutions adopted are as follows:

[0005] A photovoltaic charging control method for a UAV airport, the method comprising:

[0006] Obtain the preset inspection path, power consumption per unit inspection distance, remaining power of each UAV, and the available power of the UAV airport on the current day;

[0007] Obtain the UAVs to be charged; according to the remaining power and the available power of all the UAVs to be charged, and in combination with the lengths of the preset inspection paths and the power consumption per unit inspection distance of all the UAVs to be charged, determine whether the available power of the airport on the current day meets the inspection requirements of all UAVs;

[0008] When it is determined that the available power on the current day cannot meet all the UAV inspection requirements, select the preset inspection path of any one of the UAVs to be charged as the target path; according to the intersection characteristics between the target path and other preset inspection paths, obtain the overall replaceability degree of the target path; segment the preset inspection paths at the intersection points between the preset inspection paths to obtain segmented paths; select any one of the segmented paths in the target path as the target segmented path; according to the intersection angle and path length between the target segmented path and other intersecting segmented paths, and in combination with the corresponding overall replaceability degree, obtain the local replaceability degree of the target segmented path; control the deletion of the target segmented path according to the local replaceability degree of the target segmented path to obtain the corrected inspection path of each UAV to be charged;

[0009] According to the latest corrected inspection path of the UAV to be charged, re-obtain new UAVs to be charged. When it is re-determined that the available power on the current day cannot meet all the UAV inspection requirements, re-obtain the corrected inspection paths of the new UAVs to be charged until it is determined that the available power on the current day can meet all the UAV inspection requirements, and obtain the final inspection path of each UAV;

[0010] According to the final inspection path, remaining power, power consumption per unit inspection distance, and available power of each UAV, perform power allocation for each UAV.

[0011] Further, the method for determining whether the available power at the airport on the current day can meet all the UAV inspection requirements includes:

[0012] Take the sum value of the available power and the remaining power of all the UAVs to be charged as the total power;

[0013] Take the sum value of the products of the lengths of the preset inspection paths of all the UAVs to be charged and the power consumption per unit inspection distance as the total power demand;

[0014] When the total power is less than the total power demand, it is determined that the available power on the current day cannot meet all the UAV inspection requirements.

[0015] Further, the method for obtaining the overall replaceability degree includes:

[0016] Obtain the number of intersection points between the target path and other preset inspection paths;

[0017] Obtain the intersection angle at the intersection between the target path and other preset inspection paths; the intersection angle is the angle of the minimum intersection angle at the intersection of two inspection paths;

[0018] Obtain the overall replaceability degree of the target path according to the number of intersections corresponding to the target path and the intersection angles at all intersections; the number of intersections is positively correlated with the overall replaceability degree; the intersection angle is negatively correlated with the overall replaceability degree.

[0019] Further, the method for obtaining the local replaceability degree includes:

[0020] Select any segment path that intersects with the target segment path and belongs to other UAVs as the judgment path; use the ratio of the length of the judgment path to the length of the target segment path as the replacement coefficient;

[0021] Obtain the local replaceability coefficient of the target segment path according to the intersection angle between the target segment path and the judgment path, the replacement coefficient, and the overall replaceability degree of the target path; the intersection angle is negatively correlated with the local replaceability coefficient; both the replacement coefficient and the overall replaceability degree are positively correlated with the local replaceability coefficient; the intersection angle between the target segment path and the judgment path is the same as the intersection angle at the corresponding intersection of the preset inspection path to which the target path to which the target segment path belongs and the judgment path belongs;

[0022] Select the maximum value among the local replaceability coefficients of the target segment path and all the judgment paths as the local replaceability degree of the target segment path.

[0023] Further, the method for controlling the deletion of the target segment path according to the local replaceability degree of the target segment path and obtaining the corrected inspection path of each UAV to be charged includes:

[0024] When the local replaceability degree is greater than the first preset threshold, determine that the corresponding target segment path is deleted, and at the same time delete the segment path that is the farthest from the airport and isolated in the target path, and use the remaining path in the target path as the corrected inspection path of the corresponding UAV to be charged.

[0025] Further, when it is determined that the available power on the current day cannot meet the inspection requirements of all UAVs, if the local replaceability degrees of all the latest UAVs to be charged are less than or equal to the first preset threshold, or there are no intersections on the inspection paths corresponding to all the latest UAVs to be charged, delete the shortest segment path on the inspection paths corresponding to all the latest UAVs to be charged, and delete the segment path that is the farthest from the airport and isolated to obtain the corrected inspection path of each UAV to be charged.

[0026] Further, the method for allocating power to each UAV includes:

[0027] Multiply the length of the final inspection path of each latest drone to be charged by the power consumption per unit inspection distance, and use the product as the final required power of each latest drone to be charged; allocate power to the drones according to the final required power of each latest drone to be charged.

[0028] Further, the method for obtaining the drones to be charged includes:

[0029] When the product of the preset inspection path corresponding to the drone and the power consumption per unit inspection distance is less than the remaining power of the corresponding drone, determine that the corresponding drone is a drone to be charged.

[0030] Further, the method for re-obtaining new drones to be charged includes:

[0031] If the product of the latest corrected inspection path of the current drone to be charged and the power consumption per unit inspection distance is less than the remaining power of the corresponding drone, determine that the corresponding drone is a new drone to be charged.

[0032] The present invention also provides a photovoltaic charging control system for a drone airport, the system includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, it implements the steps of any one of the photovoltaic charging control methods for a drone airport.

[0033] The present invention has the following beneficial effects:

[0034] The present invention first obtains the preset inspection path, power consumption per unit inspection distance, remaining power of each drone, and the power supply available at the drone airport on the current day, providing a basis for analysis data; further obtains the drones to be charged, determines whether the available power supply at the airport on the current day can meet the inspection requirements of all drones, providing a decision basis for subsequent deletion of the inspection path, and finally controls the photovoltaic charging; further, when it is determined that the available power supply on the current day cannot meet the inspection requirements of all drones, according to the intersection characteristics of the target path and other preset inspection paths, obtains the overall replaceability degree of the target path, quantifies the replaceability of the target path from an overall perspective, facilitating subsequent prioritized deletion of paths with high replaceability and reducing the impact on the overall inspection area; further, according to the intersection angle and path length between the target segmented path and other segmented paths that intersect, combined with the corresponding overall replaceability degree, obtains the local replaceability degree representing the degree to which the target segmented path can be deleted from both local and overall perspectives, providing a basis for subsequent control of the deletion of the target segmented path; further, controls the deletion of the target segmented path according to the local replaceability degree of the target segmented path, obtains the corrected inspection path of each drone to be charged, and dynamically adapts to the available power supply of the energy storage module; further, repeatedly determines whether the available power supply at the airport on the current day can meet the inspection requirements of all drones, re-obtains the corrected inspection path of the newly identified drones to be charged until it is determined that the available power supply on the current day can meet the inspection requirements of all drones, obtaining the final inspection path of each drone to adapt to the limitation of the available power supply of the energy storage module and providing a basis for final optimization of power distribution; finally, performs power distribution for each drone according to the final inspection path, remaining power, power consumption per unit inspection distance, and available power supply of each drone. When it is determined that the available power supply on the current day is insufficient, the present invention analyzes the replaceability of the inspection path from both local and overall perspectives, deletes the inspection path, ensures that the inspection of key areas is not affected, improves the flexibility and adaptability of the inspection task, and enhances the energy utilization rate of the photovoltaic charging system in the drone airport. Description of the Drawings

[0035] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following described drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0036] Figure 1 It is a flowchart of a method for controlling photovoltaic charging of a drone airport provided by an embodiment of the present invention;

[0037] Figure 2 It is a schematic diagram of a preset inspection path of a drone provided by an embodiment of the present invention;

[0038] Figure 3 Schematic diagram of a preliminary pruned inspection path provided by an embodiment of the present invention;

[0039] Figure 4 Schematic diagram of a corrected inspection path provided by an embodiment of the present invention;

[0040] Figure 5 Schematic diagram of the final inspection path of an unmanned aerial vehicle provided by an embodiment of the present invention. Detailed implementation manners

[0041] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following combines the drawings and preferred embodiments to detail the specific implementation manners, structures, features and effects of a photovoltaic charging control method and system for an unmanned aerial vehicle airport according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0042] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0043] The following specifically describes the specific solutions of a photovoltaic charging control method and system for an unmanned aerial vehicle airport provided by the present invention with reference to the drawings.

[0044] In the embodiment of the present invention, it mainly analyzes whether the available power supply of the unmanned aerial vehicle airport on the current day and the remaining power of the unmanned aerial vehicles can meet the inspection requirements of all unmanned aerial vehicles; when the inspection requirements cannot be met, some inspection paths with a higher degree of substitutability for the unmanned aerial vehicles to be charged are pruned, and the unmanned aerial vehicles to be charged are re-determined based on the corrected inspection paths, and it is re-determined whether the inspection requirements can be met; until the inspection requirements are met, the pruning of the inspection paths is stopped, the final inspection paths are determined, the power is allocated to the unmanned aerial vehicles, and in the case of limited power, the inspection area is effectively inspected to improve the effective utilization rate of the electric energy of the photovoltaic power supply system.

[0045] Please refer to Figure 1 , which shows a flowchart of a photovoltaic charging control method for an unmanned aerial vehicle airport provided by an embodiment of the present invention, specifically including:

[0046] Step S1: Obtain the preset inspection path, power consumption per unit inspection distance, remaining power of each unmanned aerial vehicle, and the available power supply of the unmanned aerial vehicle airport on the current day.

[0047] To accurately and effectively control the photovoltaic charging of the UAV airport, first obtain the preset inspection path, power consumption per unit inspection distance, remaining power of each UAV, and the available power supply of the UAV airport on the current day, providing a basis for analysis data.

[0048] Please refer to Figure 2 , which shows a schematic diagram of the preset inspection path of a UAV provided by an embodiment of the present invention. Figure 2 Each line shape in it is the preset inspection path of a UAV.

[0049] It should be noted that in an embodiment of the present invention, the inspection is performed once a day, the preset inspection path of each UAV is fixed, the final inspection path is included in the preset inspection path, the configurations and functions of all UAVs are the same, and the power consumption per unit inspection distance is the same; it is set that the solar energy converted on the current day is used for the inspection task on the current day. An LSTM (Long Short-Term Memory) prediction model is established through the historical sunshine duration, temperature changes, and historical solar energy conversion efficiency. The converted electric energy of solar energy on the current day is determined according to the sunshine duration and temperature changes on the current day. Combining the remaining power in the energy storage device, the available power supply of the UAV airport on the current day is obtained. The LSTM prediction model is already a prior art. In other embodiments of the present invention, the implementer can also supplement the factors of sunshine duration and temperature changes according to weather factors such as the change of light intensity, wind speed, and wind direction in historical weather, predict the weather conditions on the current day, and finally predict the electric energy that can be converted on the current day to obtain the available power supply, which will not be elaborated here.

[0050] In another embodiment of the present invention, the implementer can also stipulate that the electric energy converted from the solar energy on the first day is only used for the inspections on the second day and later. For example, if there are 50 kWh of remaining electric energy after the first day, at most 50 kWh of electric energy can be used on the second day. The electric energy converted on the second day is only stored in the energy storage module for use in the inspections on the third day and later.

[0051] It should be noted that for extreme weather on the current day, that is, weather conditions that do not meet the requirements of UAV inspections, since the UAVs do not need to perform inspections, there is no need to allocate the power of the UAVs and it can be directly skipped.

[0052] It should be noted that since the power consumption of the UAV in the non-inspection mode is small, the present invention only considers the inspection power consumption on the inspection path and does not consider other power consumptions. It is set that the UAV starts the inspection from the end closest to the airport in the inspection path and can return along the inspection path or return in a straight line when returning. The implementer can also reserve a specific energy storage space in the energy storage device. The electric energy stored in the specific energy storage space is only used for the power consumption of the UAV in the non-inspection mode. When obtaining the available power supply of the UAV airport on the current day, the electric energy stored in the specific energy storage space is removed.

[0053] Step S2: Obtain the drones to be charged; based on the remaining power and available power of all drones to be charged, combined with the lengths of the preset inspection paths and the power consumption per unit inspection distance of all drones to be charged, determine whether the available power at the airport on the current day can meet the inspection requirements of all drones.

[0054] After obtaining the preset inspection path, the power consumption per unit inspection distance, and the remaining power of the drone, it is easy to obtain the power required for the drone to complete the preset inspection path, and then compare it with the remaining power to obtain the drones to be charged.

[0055] As an example, when the product of the preset inspection path corresponding to the drone and the power consumption per unit inspection distance is less than the remaining power of the corresponding drone, determine that the corresponding drone is a drone to be charged.

[0056] Based on the lengths of the preset inspection paths of all drones to be charged and the power consumption per unit inspection distance, it is easy to obtain the power required for the inspection. At the same time, based on the remaining power and available power of all drones to be charged, it is easy to obtain the total available power. Therefore, based on the remaining power and available power of all drones to be charged, combined with the lengths of the preset inspection paths of all drones to be charged and the power consumption per unit inspection distance, it can be determined whether the available power at the airport on the current day can meet the inspection requirements of all drones, providing a decision basis for whether to delete the inspection path subsequently, and finally controlling the photovoltaic charging.

[0057] Preferably, in an embodiment of the present invention, the sum of the available power and the remaining power of all drones to be charged is used as the total power;

[0058] The sum of the products of the lengths of the preset inspection paths of all drones to be charged and the power consumption per unit inspection distance is used as the total power demand;

[0059] When the total power is less than the total power demand, it is determined that the available power on the current day cannot meet the inspection requirements of all drones.

[0060] Step S3: When it is determined that the available power on the current day cannot meet the inspection requirements of all drones, select the preset inspection path of any drone to be charged as the target path; based on the intersection characteristics between the target path and other preset inspection paths, obtain the overall replaceability degree of the target path; segment the preset inspection paths at the intersection points between the preset inspection paths to obtain segmented paths; select any segmented path in the target path as the target segmented path; based on the intersection angle and path length between the target segmented path and other intersecting segmented paths, combined with the corresponding overall replaceability degree, obtain the local replaceability degree of the target segmented path; control the deletion of the target segmented path according to the local replaceability degree of the target segmented path to obtain the corrected inspection paths of each drone to be charged.

[0061] When it is determined that the power supply available on the same day cannot meet the inspection requirements of all drones, it is necessary to delete the preset inspection paths of the drones to be charged, reducing the power consumption of the inspection; at the same time, considering that the distribution and intersection of the preset inspection paths are different and the degrees of replaceability are different, the preset inspection path of any drone to be charged is selected as the target path, and the replaceability of the target path is analyzed.

[0062] Considering that when a drone conducts inspections on an inspection path, it has a certain inspection range, similar to a road sprinkler having a certain sprinkling range when operating, when the inspection paths of drones intersect, there are overlapping inspection areas. Therefore, according to the intersection characteristics of the target path and other preset inspection paths, the overall replaceability of the target path is obtained, quantifying the replaceability of the target path from an overall perspective, facilitating the subsequent prioritized deletion of paths with high replaceability, reducing the impact on the overall inspection area, improving the flexibility and adaptability of the inspection task, and enhancing the energy utilization rate of the photovoltaic charging system in the drone airport.

[0063] Preferably, in an embodiment of the present invention, considering that the more intersection points there are between the target path and other inspection paths, it indicates that the overlap degree of the inspection areas of the target path and other inspection paths is higher and it is more replaceable, and the number of intersection points is positively correlated with the overall replaceability; considering that the smaller the intersection angle between two paths, the more the overlapping range of the inspection areas, so the intersection angle is negatively correlated with the overall replaceability;

[0064] Based on this, the number of intersection points between the target path and other preset inspection paths is obtained;

[0065] The intersection angle at the intersection of the target path and other preset inspection paths is obtained; the intersection angle is the angle of the minimum intersection angle at the intersection of two inspection paths;

[0066] According to the number of intersection points corresponding to the target path and the intersection angles at all intersections, the overall replaceability of the target path is obtained.

[0067] As an example, the unit of the intersection angle is degrees, and the calculation formula for the overall replaceability includes:

[0068]

[0069] where, v represents the serial number of the target path; y v represents the overall replaceability of the v-th target path; N v represents the number of intersection points between the v-th target path and other preset inspection paths; θ v,iDenote the intersection angle at the $i$-th intersection of the $v$-th target path and other preset inspection paths; $\sin()$ represents the sine function; $c$ represents a preset positive parameter for dividing by zero, and in this example $c = 0.1$.

[0070] In the calculation formula of the overall replaceability degree, the intersection angle is mapped through the sine function. Since the intersection angle is the angle of the minimum intersection angle at the intersection of two inspection paths, the intersection angle is greater than or equal to $0^{\circ}$ and less than or equal to $90^{\circ}$. In this value range, the larger $\theta$ v,i , the larger $\sin(\theta$ v,i ). Then, by means of taking the reciprocal for negative correlation mapping to adjust the logical relationship, the larger $\theta$ v,i , the smaller the overlapping range of the inspection area and the smaller the overall replaceability degree; $N$ v is in the numerator position. The larger $N$ v , that is, the more intersection points, it indicates that the overlapping degree of the inspection areas of the target path and other inspection paths is higher, and the overall replaceability degree is larger.

[0071] In other embodiments of the present invention, the implementer can also use the exponential function $\exp(-x)$ with the natural constant $e$ as the base for negative correlation mapping, such as where $x$ represents the independent variable.

[0072] Considering that directly deleting the entire target path is likely to remove too many inspection paths at once, which is not conducive to ensuring the completion of the inspection task. Therefore, the preset inspection paths are segmented at the intersection points between the preset inspection paths to obtain segmented paths; select any segmented path in the target path as the target segmented path; analyze from a local perspective. Also considering that the replaceability of the target segmented path is related to the intersection angle, and at the same time considering that the replaceability of the target segmented path is also related to its own path length and the path lengths of other segmented paths it intersects with, and the larger the overall replaceability degree of itself also indicates the greater the replaceability of the target segmented path. Therefore, according to the intersection angle and path length of the target segmented path and other segmented paths it intersects with, combined with the corresponding overall replaceability degree, the local replaceability degree of the target segmented path is obtained.

[0073] Preferably, in an embodiment of the present invention, considering that the target segmented path may intersect with multiple segmented paths belonging to other unmanned aerial vehicles. For example, the target segmented path belongs to unmanned aerial vehicle A, and the path endpoints are A and B. The path endpoint A intersects with two segmented paths belonging to unmanned aerial vehicle B, and the path endpoint B intersects with one segmented path belonging to unmanned aerial vehicle C. Therefore, first select any segmented path that intersects with the target segmented path and belongs to other unmanned aerial vehicles as the judgment path for analysis one by one;

[0074] Considering that the smaller the intersection angle between the determination path and the target segmented path, the closer it is to being parallel, the easier it is for the determination path to cover the inspection area of the target segmented path. At the same time, the longer the determination path is relative to the target segmented path, the greater the coverage of the current determination path in this local area during inspection, the larger the range of the possibly overlapping inspection areas in the target segmented path, and the smaller the impact of deleting the target segmented path on the inspection task, and the stronger the substitutability. Based on this, the ratio of the length of the determination path to the length of the target segmented path is used as the replacement coefficient;

[0075] According to the intersection angle between the target segmented path and the determination path, the replacement coefficient, and the overall substitutability of the target path, obtain the local substitutability coefficient of the target segmented path; the intersection angle is negatively correlated with the local substitutability coefficient; both the replacement coefficient and the overall substitutability are positively correlated with the local substitutability coefficient; the intersection angle between the target segmented path and the determination path is the same as the intersection angle between the target path to which the target segmented path belongs and the preset inspection path to which the determination path belongs at the corresponding intersection;

[0076] Select the maximum value among the local substitutability coefficients of the target segmented path and all determination paths as the local substitutability degree of the target segmented path.

[0077] As an example, the calculation formula for the local substitutability degree includes:

[0078]

[0079] where, v represents the serial number of the target path; k represents the serial number of the segmented path of the target path; j represents the serial number of the determination path of the target segmented path; t v,k,j represents the local substitutability coefficient corresponding to the k-th target segmented path of the v-th target path and the j-th determination path; y v represents the overall substitutability degree of the v-th target path; L j represents the path length of the j-th determination path; L v,k represents the path length of the k-th target segmented path of the v-th target path; represents the replacement coefficient corresponding to the k-th target segmented path of the v-th target path and the j-th determination path; θ v,k,j represents the intersection angle corresponding to the k-th target segmented path of the v-th target path and the j-th determination path; d represents a preset positive parameter for dividing by zero, and in this example, d = 0.05; softmax{} represents the softmax function; cos() represents the cosine function.

[0080] In the calculation formula of the local replaceability degree, the greater the overall replaceability degree, it indicates that from the overall analysis of the target path, the stronger the replaceability and the greater the local replaceability degree. Since the intersection angle between the target segmented path and the determination path is the same as the intersection angle between the target path to which the target segmented path belongs and the preset inspection path to which the determination path belongs at the corresponding intersection, the intersection angle between the target segmented path and the determination path is greater than or equal to 0° and less than or equal to 90°. Within this value range, the larger the θ v,k,j , the smaller cos(θ v,k,j ), and the greater the local replaceability degree. Since the intersection angle may be 90°, to avoid the term being meaningless when the intersection angle is 90°, a parameter d is set to adjust the value range of cos(θ v,k,j ). The larger the replacement coefficient, it indicates that the determination path is longer relative to the target segmented path, the possible overlapping inspection area is larger, the impact of deleting the target segmented path on the inspection task is smaller, the stronger the replaceability, and the greater the local replaceability degree.

[0081] In other embodiments of the present invention, the implementer can also use the sine function to perform a negative correlation mapping and then obtain the local replaceability degree, such as

[0082] It should be noted that when there is no intersection point in the selected target path, the target path is the target segmented path, and both the overall replaceability degree and the local replaceability degree are 0.

[0083] After evaluating the replaceability of the target segmented path from both local and overall perspectives to obtain the local replaceability degree representing the degree to which the target segmented path can be deleted, the deletion of the target segmented path can be controlled according to the local replaceability degree of the target segmented path, and the corrected inspection path of each drone to be charged can be obtained to dynamically adapt to the power supply capacity of the energy storage module.

[0084] Preferably, in an embodiment of the present invention, considering that the greater the local replaceability degree, the more the corresponding segmented path can be deleted, when the local replaceability degree is greater than the first preset threshold, it is determined that the corresponding target segmented path is deleted. Since isolated segmented paths may be left after deletion, for the continuity of the inspection task, the segmented path that is the farthest from the airport and isolated in the target path is also deleted, and the remaining path in the target path is used as the corrected inspection path of the corresponding drone to be charged.

[0085] Please refer to Figure 3 , which shows a schematic diagram of a preliminary deleted inspection path provided by an embodiment of the present invention. Figure 3 In Figure 4, which shows a schematic diagram of a modified inspection path provided by an embodiment of the present invention. Figure 4 Deleted Figure 3 the segmented path that is the farthest from the airport and isolated in

[0086] In another embodiment of the present invention, the implementer can also retain Figure 3 the segmented path that is the farthest from the airport and isolated in

[0087] Step S4: According to the latest modified inspection path of the drones to be charged, re-obtain new drones to be charged. When it is re-determined that the available power on the same day cannot meet the inspection requirements of all drones, re-obtain the modified inspection path of the new drones to be charged until it is determined that the available power on the same day can meet the inspection requirements of all drones, and obtain the final inspection path of each drone.

[0088] After the inspection path is deleted in step S3, the inspection energy consumption requirements of the current drones to be charged are reduced. At this time, the remaining power of some of the current drones to be charged may already meet the corresponding modified inspection path. Therefore, according to the latest modified inspection path of the drones to be charged, re-obtain new drones to be charged; re-perform step S2 based on the newly obtained drones to be charged to determine whether the available power at the airport on the same day can meet the inspection requirements of all drones; when it is re-determined that the available power on the same day cannot meet the inspection requirements of all drones, perform step S3 again, delete again on the basis of the current modified inspection path, re-obtain the modified inspection path of the new drones to be charged, and loop through steps S2 - S3 to gradually reduce the charging requirements of all drones until it is determined that the available power on the same day can meet the inspection requirements of all drones. At this time, the power consumption requirements of the final modified inspection path can be met, and the final inspection path of each drone is obtained.

[0089] For example, it is initially determined that drones A and C are both drones to be charged. Obtain the modified inspection paths of A and C through step S3. At this time, the remaining power of A can meet the current modified inspection path, while C still cannot. At this time, C is re-determined as a new drone to be charged, and the mark of the drone to be charged is removed from A. Finally, the inspection path of A is the current modified inspection path, and C participates again in determining whether the available power at the airport on the same day can meet the inspection requirements of all drones.

[0090] It should be noted that in an embodiment of the present invention, considering that when it is determined that the available power on the current day cannot meet the inspection requirements of all unmanned aerial vehicles (UAVs), if the local replaceability degrees of all the latest UAVs to be charged are less than or equal to the first preset threshold, or there are no intersection points on the inspection paths corresponding to all the latest UAVs to be charged, the execution condition of step S3 is not satisfied, and the path cannot be cyclically deleted again by the method of step S3. At this time, considering that the shorter the segmented path of the latest UAVs to be charged, the smaller the impact on the overall inspection task after deletion, so the shortest segmented path on the inspection paths corresponding to all the latest UAVs to be charged is deleted, and the segmented path that is the farthest from the airport and isolated is deleted to obtain the corrected inspection path for each UAV to be charged. As an example, the first preset threshold is 0.8.

[0091] Similarly, in another embodiment of the present invention, the implementer can also retain the segmented path that is the farthest from the airport and isolated.

[0092] It should be noted that when the UAVs to be charged are first obtained on the current day, since the remaining power of the UAVs not determined to be UAVs to be charged can already meet the inspection requirements of the corresponding preset inspection paths, the preset inspection paths are directly used as the final inspection paths.

[0093] Please refer to Figure 5 , which shows a schematic diagram of the final inspection path of a UAV provided by an embodiment of the present invention. Compared with Figure 2 , Figure 5 the inspection paths of two UAVs are deleted to adapt to the limitation of the available power of the energy storage module.

[0094] Step S5: Perform power allocation for each UAV according to the final inspection path, remaining power, power consumption per unit inspection distance, and available power of each UAV.

[0095] After finally determining the final inspection path of each UAV, the charging requirements of the UAV can be obtained based on the remaining power and power consumption per unit inspection distance of the final inspection path, the photovoltaic charging can be controlled, and the available power can be allocated to each UAV to perform the inspection task on the current day.

[0096] Preferably, in an embodiment of the present invention, the product of the length of the final inspection path and the power consumption per unit inspection distance of each latest UAV to be charged is used as the final required power of each latest UAV to be charged; the UAVs are power-allocated according to the final required power of each latest UAV to be charged.

[0097] It should be noted that, except for the latest drone to be charged, the final required power of other drones is 0; the photovoltaic power generation module converts solar energy into electrical energy and transmits it to the energy storage module. The charge control module obtains the available power of the energy storage module on the current day and the final required power of each latest drone to be charged, and performs power distribution; the stored electrical energy is output at 220V and 50Hz through the inverter module to charge the latest drone to be charged.

[0098] It should be noted that the performance of the drone battery needs to be tested regularly, including capacity, voltage and health status, to ensure that the battery can provide the required power for the completion of the inspection task.

[0099] An embodiment of the present invention also provides a photovoltaic charging control system for a drone airport, which includes a memory, a processor and a computer program. The memory is used to store the corresponding computer program, and the processor is used to run the corresponding computer program. When the computer program runs in the processor, it can implement a photovoltaic charging control method for a drone airport described in steps S1 - S5.

[0100] In summary, to solve the technical problem of intelligent control of photovoltaic charging to ensure the inspection effect, the present invention first obtains the preset inspection path, power consumption per unit inspection distance, remaining power of each drone, and the available power of the drone airport on the current day; further, it repeatedly obtains the drones to be charged and determines whether the available power of the airport on the current day can meet the inspection requirements of all drones; when it is determined that the available power on the current day cannot meet the inspection requirements of all drones, it obtains the local replaceability degree of the target segmented path; controls the deletion of the target segmented path according to the local replaceability degree of the target segmented path to obtain the corrected inspection path of each drone to be charged until it is determined that the available power on the current day can meet the inspection requirements of all drones, and obtains the final inspection path of each drone; finally, according to the final inspection path, remaining power, power consumption per unit inspection distance and available power of each drone, power distribution is carried out for each drone. When the present invention determines that the available power on the current day is insufficient, by analyzing the replaceability of the inspection path from both local and overall perspectives, the inspection path is deleted to ensure that the inspection of key areas is not affected, improve the flexibility and adaptability of the inspection task, and enhance the energy utilization rate of the photovoltaic charging system in the drone airport.

[0101] It should be noted that the above sequence of embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0102] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the key point of each embodiment is to illustrate the differences from other embodiments.

Claims

1. A photovoltaic charging control method for a drone airport, characterized in that: The method comprises: Obtain the preset inspection route of each drone, the power consumption per inspection distance, the remaining power, and the power available at the drone airport on that day; Obtain the drones to be charged; determine whether the power supply at the airport on that day meets the inspection needs of all drones based on the remaining power and the available power of all the drones to be charged, combined with the length of the preset inspection paths of all the drones to be charged and the power consumption per inspection distance; When it is determined that the power supply on that day cannot meet the inspection needs of all drones, the preset inspection path of any drone to be charged is selected as the target path; the overall substitutability of the target path is obtained according to the intersection characteristics of the target path and other preset inspection paths; the preset inspection path is segmented at the intersection points between the preset inspection paths to obtain segmented paths; any segmented path in the target path is selected as the target segmented path; the local substitutability of the target segmented path is obtained according to the intersection angle and path length between the target segmented path and other intersecting segmented paths, combined with the corresponding overall substitutability; the deletion of the target segmented path is controlled according to the local substitutability of the target segmented path, and the revised inspection path of each drone to be charged is obtained; According to the latest revised inspection path of the drone to be charged, a new drone to be charged is obtained again. When it is re-determined that the power supply on that day cannot meet the inspection needs of all drones, the revised inspection path of the new drone to be charged is obtained again, until it is determined that the power supply on that day can meet the inspection needs of all drones, and the final inspection path of each drone is obtained; Power is allocated to each drone according to the final inspection path, the remaining power, the power consumption per inspection distance and the available power of each drone.

2. The photovoltaic charging control method for a drone airport according to claim 1 is characterized in that: The method for determining whether the power supply at the airport on that day meets the inspection requirements of all drones includes: The sum of the available power and the remaining power of all the drones to be charged is taken as the total power; The sum of the products of the lengths of the preset inspection paths of all the drones to be charged and the power consumption per unit inspection distance is taken as the total power demand; When the total power is less than the total power demand, it is determined that the available power on that day cannot meet all drone inspection needs.

3. The photovoltaic charging control method for a drone airport according to claim 1 is characterized in that: The method for obtaining the overall degree of substitutability includes: Obtaining the number of intersections between the target path and other preset inspection paths; Obtaining an intersection angle at the intersection of the target path and the other preset inspection paths; the intersection angle is the minimum intersection angle at the intersection of the two inspection paths; The overall degree of substitutability of the target path is obtained according to the number of intersections corresponding to the target path and the intersection angles at all intersections; the number of intersections is positively correlated with the overall degree of substitutability; and the intersection angle is negatively correlated with the overall degree of substitutability.

4. The photovoltaic charging control method for a drone airport according to claim 3 is characterized in that: The method for obtaining the local substitutability degree includes: Select any segmented path that intersects with the target segmented path and belongs to other UAVs as a determination path; use the ratio of the length of the determination path to the length of the target segmented path as a replacement coefficient; According to the intersection angle between the target segmented path and the determination path, the replacement coefficient and the overall degree of substitution of the target path, a local substitution coefficient of the target segmented path is obtained; the intersection angle is negatively correlated with the local substitution coefficient; the replacement coefficient and the overall degree of substitution are both positively correlated with the local substitution coefficient; the intersection angle between the target segmented path and the determination path is the same as the intersection angle between the target path to which the target segmented path belongs and the preset inspection path to which the determination path belongs at the corresponding intersection; The maximum value of the local substitutability coefficients of the target segment path and all the determination paths is selected as the local substitutability degree of the target segment path.

5. The photovoltaic charging control method for a drone airport according to claim 4 is characterized in that: The method of controlling the deletion of the target segmented path according to the local replaceability degree of the target segmented path to obtain the corrected inspection path of each of the unmanned aerial vehicles to be charged includes: When the local replaceability is greater than a first preset threshold, it is determined that the corresponding target segmented path is deleted, and at the same time, the segmented path farthest from the airport and isolated in the target path is deleted, and the remaining path in the target path is used as the corrected inspection path corresponding to the drone to be charged.

6. The photovoltaic charging control method for a drone airport according to claim 5 is characterized in that: When it is determined that the power supply on that day cannot meet the inspection needs of all drones, if the local substitutability of all target segmented paths of all the latest drones to be charged is less than or equal to the first preset threshold, or there is no intersection on the inspection path corresponding to all the latest drones to be charged, the shortest segmented path on the inspection path corresponding to all the latest drones to be charged is deleted, and the segmented path farthest from the airport and isolated is deleted to obtain a corrected inspection path for each drone to be charged.

7. The photovoltaic charging control method for a drone airport according to claim 1 is characterized in that: The method for distributing power to each drone includes: The product of the length of the final inspection path of each latest drone to be charged and the power consumption per unit inspection distance is used as the final power requirement of each latest drone to be charged; and power is allocated to the drones according to the final power requirement of each latest drone to be charged.

8. The photovoltaic charging control method for a drone airport according to claim 1 is characterized in that: The method for obtaining the drone to be charged includes: When the product of the preset inspection path corresponding to the drone and the power consumption per unit inspection distance is less than the remaining power of the corresponding drone, the corresponding drone is determined to be a drone to be charged.

9. The photovoltaic charging control method for a drone airport according to claim 1 is characterized in that: The method for reacquiring a new drone to be charged includes: If the product of the latest revised inspection path of the current drone to be charged and the power consumption per unit inspection distance is less than the remaining power of the corresponding drone, the corresponding drone is determined to be a new drone to be charged.

10. A photovoltaic charging control system for an unmanned aerial vehicle airport, the system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the photovoltaic charging control method for an unmanned aerial vehicle airport as described in any one of claims 1 to 9 are implemented.

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